Coronary heart disease (CHD), also referred to as ischemic heart disease, is a life-threatening cardiovascular disorder pathologically characterized by an imbalance between myocardial oxygen demand and coronary blood supply. Significant reduction in coronary perfusion or impairment of vasomotor function may lead to sustained myocardial hypoxia, thereby precipitating acute clinical events such as myocardial infarction [1]. Epidemiologic studies indicate that middle-aged and elderly populations exhibit elevated incidence and mortality rates of CHD, with prevalence exceeding 27.8% among adults aged over 60 years [2]. Notably, age-related physiological decline heightens susceptibility to metabolic abnormalities in this demographic. This process is typically accompanied by insulin resistance (IR), which exacerbates systemic metabolic dysregulation and contributes to a cascade of pathophysiological alterations—including endothelial dysfunction, chronic inflammation, and platelet hyperactivation—all of which collectively amplify cardiovascular risk [3]. Furthermore, elderly CHD patients typically demonstrate a higher burden of comorbidities and consequently experience poorer clinical outcomes compared to their younger counterparts.

IR is a pathophysiological state characterized by diminished insulin sensitivity in peripheral tissues, leading to impaired glucose uptake and utilization. Substantial evidence has established strong associations between IR and the pathogenesis of various diseases, including ischemic stroke [4], sepsis [5], and multiple cardiovascular disorders [6]. Notably, the triglyceride-glucose index (TyG), an emerging biomarker for IR assessment, has been demonstrated to correlate significantly with arterial elasticity, the extent of coronary atherosclerosis, and neurological deficit scores in patients with cerebral infarction [7]. Chronic inflammation has been identified as a critical contributor to CHD pathogenesis. Inflammation-induced endothelial dysfunction promotes subendothelial lipoprotein retention, leukocyte recruitment, and enhanced vascular permeability mediated by platelet activation [8], collectively facilitating fibroatheroma development. In this context, Ruan et al. [9] innovatively proposed the C-reactive protein-triglyceride-glucose index (CTI) in 2022. This composite biomarker integrates inflammatory markers (C-reactive protein) with parameters of IR (TyG index). Although initially applied for prognostic evaluation in oncology, this multidimensional approach offers novel perspectives for assessing metabolic and inflammation-related diseases.

Studies have demonstrated that IR is independently associated with cardiovascular events in both diabetic (DM) and non-diabetic (NDM) individuals. Furthermore, accumulating evidence indicates that IR is linked to subclinical vascular damage, which manifests as functional and structural alterations of the arterial wall that cannot be fully explained by conventional risk factors [10]. Currently, coronary angiography remains the gold standard for clinically diagnosing CHD and assessing the severity of coronary artery lesions. Based on angiographic findings, this study aims to quantify the extent of coronary artery lesions, identify factors influencing CHD development in elderly patients, and investigate the association between CTI and both CHD prevalence and severe coronary lesions across varying glucose metabolism statuses. The ultimate objective is to establish a practical and efficient screening tool to facilitate early identification of elderly CHD patients and high-risk individuals.

Our findings demonstrate that CTI is an independent risk factor for CHD in elderly populations (OR = 4.88, 95% CI: 3.59–6.62). As a novel composite biomarker integrating CRP and TyG index, CTI provides a holistic assessment of both inflammatory status and IR severity. Unlike CRP or TyG alone, which reflect isolated pathophysiological dimensions, CTI captures synergistic or compensatory interactions between inflammation and IR, thereby improving risk stratification accuracy. The complementary roles of these biomarkers—reflecting inflammatory activity and metabolic dysfunction, respectively—enhance the identification of high-risk profiles while mitigating the limitations of individual biomarker variability. This mechanistic rationale is corroborated by the significant association between CTI and CHD observed in our study, which aligns with previous reports by Xu et al. [14] indicating a 1.357-fold increase in CHD risk per standard deviation rise in CTI. Importantly, CTI represents a readily accessible, cost-effective clinical tool that holistically reflects inflammatory-metabolic dysregulation. Its simplicity and robustness support its potential utility in routine screening for elevated CHD risk in elderly populations.

Our study further revealed that CTI remained significantly associated with CHD incidence across different glucose metabolic states. When analyzed as a continuous variable, CTI demonstrated a clear dose-response relationship with CHD occurrence in elderly populations—a trend that persisted when CTI was categorized into quartiles (Q1–Q4). ROC curve analysis consistently confirmed the discriminative capacity of CTI for CHD risk stratification, irrespective of glycemic status. Notably, CTI exhibited superior predictive performance in patients of DM (AUC: 0.834), suggesting an enhanced prognostic utility under conditions of pronounced metabolic dysregulation. Both subgroup analyses and RCS curves consistently indicated a strong positive association between CTI and CHD risk in elderly individuals. This relationship remained significant after comprehensive adjustment for multiple confounders and proved stable across all predefined stratification variables. Furthermore, CTI showed significant positive correlations with the severity of coronary artery stenosis, particularly among patients with DM and those with pre-DM.

Our findings indicate that elderly individuals exhibit significantly reduced vascular elasticity and more impaired endothelial function compared to younger populations. These age-related structural and functional changes, compounded by chronic low-grade inflammation and elevated oxidative stress, collectively promote lipid deposition and accelerate atherosclerotic plaque formation. In patients with DM or pre-DM, disordered glucose metabolism further exacerbates atherosclerosis through multiple synergistic pathways. A self-amplifying cycle emerges involving hyperglycemia-induced endothelial dysfunction, dyslipidemia, and IR-related metabolic dysregulation. Importantly, aging potentiates IR through heightened inflammatory responses and oxidative stress, while IR in turn aggravates vascular dysfunction via endothelial impairment and enhanced inflammation—establishing a pathogenic “aging–IR–atherosclerosis” triad that drives accelerated CHD progression [2]. At the mechanistic level, insulin-resistant adipose tissue dysfunction promotes systemic inflammation via increased release of proinflammatory cytokines (e.g., TNF-$\alpha$, IL-6), fostering a microenvironment conducive to monocyte infiltration and foam cell formation, which are critical to atherosclerotic lesion development [15].

These mechanisms account for the superior predictive performance of CTI in DM patients, as diabetic metabolic dysregulation likely amplifies the synergistic vascular damage associated with both aging and CTI. The lack of a significant CTI–CHD correlation in normoglycemic individuals may be attributed to: (1) the dependency of CTI’s atherogenic effects on diabetes-specific metabolic disturbances such as chronic inflammation and IR [16]; (2) preserved insulin-mediated vasoprotective mechanisms under normoglycemic conditions; and (3) compensatory hyperinsulinemia that maintains metabolic equilibrium in subjects with intact $\beta$-cell function [17]. These findings collectively suggest that the cardiovascular implications of CTI follow a threshold effect, becoming clinically discernible only when glucoregulatory impairment reaches a critical severity.

We developed a predictive nomogram model that integrates CTI with other key clinical variables. Multivariate logistic regression identified CTI, male sex, LDL cholesterol, diabetes history, and white blood cell count as independent risk factors, collectively constituting a comprehensive risk assessment system for CHD in elderly patients. This geriatric-specific model innovatively combines conventional cardiovascular risk factors [18]—such as male sex and elevated LDL—with inflammatory markers (e.g., White Blood Cells count) and the novel CTI index, which concurrently captures insulin resistance and inflammatory activity. The synergistic interplay among these multidimensional components substantially enhances the model’s discriminative capacity and predictive accuracy.

The well-established association between inflammatory biomarkers and CHD risk [19] is mechanistically substantiated in our model. Specifically, an elevated WBC count—serving as a direct marker of systemic inflammation—reflects a chronic subclinical inflammatory state that drives vascular endothelial dysfunction and promotes atherosclerotic plaque destabilization. Moreover, our model demonstrates that metabolic disturbances stemming from islet dysfunction can significantly impair cardiovascular health even during the pre-diabetes stage. This finding is consistent with clinical reports of elevated cardiovascular risk in pre-diabetic populations [20], highlighting the importance of early metabolic assessment and intervention beyond overt diabetes.

This study has some unavoidable limitations. First, as a single-center investigation, the absence of data from other regions or countries may introduce potential selection bias. Moreover, the model was developed and validated solely within this single-center cohort, which currently restricts its broader applicability. Consequently, the generalizability of our findings to wider populations or diverse clinical settings remains to be established. In future research, we intend to conduct multi-center external validation studies to rigorously evaluate the model’s stability and performance. Additionally, the relatively short time interval between coronary angiography and CTI measurement, while ensuring data timeliness, may not adequately capture the natural progression of coronary atherosclerosis. Future studies could extend the observation period or employ longitudinal designs to further validate and contextualize our results.

CTI demonstrates a positive correlation with CHD risk among elderly populations across varying glucose metabolism statuses, showing significant associations with coronary artery stenosis severity in both DM and pre-DM groups. These findings suggest that CTI serves as a reliable biomarker for predicting CHD incidence and coronary stenosis severity in elderly individuals, irrespective of their glucose metabolic status.

The datasets used and analysed during the current study are available from the corresponding author on reasonable request.

QYS, YFD: writing-original draft, data collection and analysis, funding acquisition, writing-review & editing; YZ, ZF, JJ, SHH: data curation, data collection and analysis, software, investigation; JZ: investigation, methodology, writing - review & editing, project administration. All authors contributed to editorial changes in the manuscript. All authors read and approved the final manuscript. All authors have participated sufficiently in the work and agreed to be accountable for all aspects of the work.

The study was carried out in accordance with the guidelines of the Declaration of Helsinki. The study protocol has been approved by Medical Ethics Committee of Northern Jiangsu People’s Hospital (NO: 2025ky170). Patients’ informed consent was waived due to the retrospective design.

We would like to express our gratitude to all those who helped us during the writing of this manuscript. Thanks to all the peer reviewers for their opinions and suggestions.

This study was financially supported by Postgraduate Research & Practice Innovation Program of Jiangsu Province (NO: SJCX25_2401; SJCX24_2350).

The authors declare no conflict of interest.